This invention relates to calibration of arrays of direction finding antennas and more particularly to antenna array calibration using a reduced set of sampling frequencies.
The inherent accuracy of correlation interferometer direction finding, CIDF, algorithms is described by characterizing all the direction finding antenna array responses in terms of amplitude, and phase or IandQ. In order to characterize the array, one develops a system resident, direction finding, DF database array manifold that contains the antenna responses. This characterization process is called calibration. Calibration data is measured and recorded over many frequencies and azimuths for selected elevation/depression angles and polarizations depending on the DF system requirements in order to produce a DF manifold or database.
Array manifold development is generally obtained by measuring and recording antenna data from the DF array installed on the ship, editing the data to filter out bad measurements, interpolating the data to produce the required array manifold azimuth distribution, and formatting the data for system installation.
In the past, there were two test measurements that were used to generate the array manifold. The first measurement was a surface wave measurement which involved measuring the antenna array response to signals originating from a known location that follow the curvature of the earth from on-shore. The second set of calibration values came from sky wave measurements which measure the response of the array to signals that are reflected by the ionosphere down to the antenna array. Since it is impractical to measure sky wave response on a ship, calibration, in the past, has involved the use of brass ship models which are {fraction (1/48)}th scale models of the ships in question. In order to do the calibration, the scale model is provided with loop type antennas at the positions about the ship that mimic those for the full-scale platform.
The scale model is then rotated relative to a calibration source so as to provide the surface wave and sky wave data. These measurements are taken at all frequencies of interest, which typically number 90 in a band from 1 MHz to 30 MHz.
There is, however, a difference between the results from the model and those from the full-scale platform or ship. In order to adjust the results from the model to match those of the ship, a complex optimization procedure is used which involves generating complex weights that are used to correct the response of the scale model array so that it corresponds to the shipboard array.
Key to making sure that direction-finding using such an array is effective, calibration procedures involve the selection of a number of frequencies at which signals are expected to arrive. As mentioned above, typically 90 such frequencies cover a range of 1 MHz and 30 MHz. It will be appreciated that with respect to surface wave calibration, the calibration antenna must transmit signals at these 90 frequencies to the ship, and the response of the shipboard antenna array is measured for each of these frequencies at 2xc2x0 increments in azimuth angle so that a database called an array manifold is created.
In order for all 90 frequencies to be sampled at 360 different azimuth angles, a ship can be on station for as long as 36 hours. To obtain the required data, the ship must steam in circles, for instance, ten miles away from a shore station that is transmitting calibration signals so that the response of the shipborne array can be measured. These measurements are then used with surface wave and sky wave measurements from the scale model to generate an array manifold or database. Signals from the antenna array aboard the ship are subsequently used to generate complex weights which will adjust the model array response such that when these normalized signals are passed to a direction finding algorithm, the result is an accurate line of bearing angle between the ship and the electromagnetic source.
Note that once the surface wave components of the calibration have been generated at sea, the resulting characterization array is used in combination with the scale model to generate the weights for a full complement of frequencies for both surface waves and sky waves. Thus, having characterized the shipboard array and having data from the corresponding scale model, it is then possible to calculate weights which are to be applied to the model array data so as to correct them or normalize them to be able to be used by the direction finding system on the ship.
The problem with this calibration method is that getting the surface wave measurements at sea takes a long time. This is because ship must be rotated through a full 360xc2x0 for each sampling frequency.
In order to eliminate having to sample all frequencies which are deemed to be important on a shipboard calibration run, it has been found that the weights associated with selected frequencies are valid across a wide bandwidth. This means that weights generated at one frequency are valid for a number of adjacent frequencies. As a result, the number of frequencies involved in the shipboard calibration phase can be reduced by as much as 80%.
Were the bandwidth of the complex weights at all frequencies uniform and linear, then all that would be necessary would be to simply divide up the total bandwidth into a convenient subset of equally-spaced frequencies. However, due to scattering and edge effects as well as other topographical artifacts associated with the ship, during the initial placement of the antennas, a frequency regime is set up in which the frequencies at which calibration measurements are specified. These frequencies are more dense in some regions, whereas in other regions, there is a less dense number of calibration frequencies.
It has been found that the complex weights to be specified in the manifold or dataset are useful over a broad range of frequencies. Thus, weights for one frequency will work over a number of adjacent frequencies. As a result, one can get broadband performance out of a set of complex weights. Whereby the complex weights need be provided only for a reduced set of the originally specified calibration frequencies.
For shipboard calibration measurement in order to reduce the total number of frequencies to about 15-20% of the original number, one must be careful not to remove too many frequencies in regions where the density of calibration frequencies is high. The density of calibration frequencies is high when there are resonances causing the antenna patterns to change very quickly. Here it is necessary to provide a larger number of calibration frequencies, although still less than the original number of calibration frequencies determined from a scale model of the ship. Where there are less dense frequencies even less numbers of calibration frequencies need to be provided. What this means is that one is culling the calibration frequencies at which one wants to sample and eliminates those frequencies based on the characteristics of the antenna array and the topside configuration of the ship.
As to what calibration frequencies are initially picked, and from which one can ascertain frequency density, the frequencies picked relate to direction finding error based on the results of direction finding using the original model. This results in a set of calibration frequencies.
How this is done is as follows: Considering a frequency of interest that is halfway between two frequencies, there is going to be a direction finding error associated with it because one is not on the calibration frequency anymore. How far a target frequency can be from a calibration frequency and still be within an acceptable DF error defines band edge error. When the band edge error is above some limit, one needs to add another calibration frequency. Thus band edge error establishes frequency density.
It has been found that more dense calibration frequency densities occur when antenna array patterns are changing quite rapidly with frequency. Less dense frequencies occur there the array patterns change slowly. As a result, one can eliminate a large number of calibration frequencies used in frequency bands where the antenna pattern characteristics are not changing very quickly. The antenna characteristics which are changing slowly are those whose amplitude and phase patterns and the ensemble characteristics of the entire direction finding array vary little with frequency and azimuth.
One, however, cannot drop large numbers of frequencies where all the antennas are changing so fast that the bandwidth of the complex weights for the array manifold becomes reduced. What this means is that the antenna patterns are changing very fast with respect to azimuth and frequency on board the ship, with the changes being a function of the scattering from different superstructure configurations, topside configurations and antennas that may be in the area. When all of these configurations start to resonate, inter-resonances can affect neighboring antennas, therefore making the patterns change very quickly. Thus, in some frequency bands, the patterns change much more rapidly than others because of these resonances.
The result is that if, for instance, one has one region of very dense frequencies, and the remainder not dense at all, one could have 10 frequencies in the dense frequency zone and 5 frequencies spread out over the rest of the band. Thus, sampling at only 15 frequencies, as opposed to 90 frequencies is sufficient for the calibration process.
More particularly, calibration for sky wave direction finding involves the use of a combination of platform and scale model data to form an array manifold or database required for correlation interferometer direction finding and polarization independent correlation interferometer direction finding correlation interferometer direction finding CIDF algorithms. In one embodiment, multi-dimensional arrays are comprised of DF antenna measurements recorded over frequency, azimuth, elevation and polarization. Calibration is normally performed in two stages, with the first stage being an at sea calibration which forms the surface wave segment of the array manifold. The second stage is the sky wave calibration required for polarization independent CIDF algorithms. The sky wave calibration process characterizes the DF antenna responses over frequency, azimuth and elevation angle for both vertical and horizontal polarization. If the antenna array response were linear than one could simply equally divide the number of frequencies at which data is collected by some number. However, due to scatter and edge characteristics, the original density of sampling frequencies is taken into account, with the reduced set of frequencies having increased numbers of components for dense sets of frequencies, and an even further reduced set of frequencies for less dense sets of frequencies. Thus, shipboard calibration exercises which typically involved one or more days, can now be reduced to a matter of hours, with the remainder of the data being derived from scale model testing such that the array manifold or data set used aboard the ship is a result more of scale model testing than it is of shipboard testing.
One way to find out initially as to where the antenna characteristics change rapidly is to make an initial sweep of all of the azimuths and measure what is actually happening with the antenna pattern in terms of amplitude and phase versus azimuth.
This type of analysis can be done using a scale model that is part of the model study that is used to define the best antenna locations for that ship. This is the process that indicates what calibration frequencies are needed for the particular shipboard platform.
The way that one understands what frequencies need to be sampled and the ones that can be ignored is to take the original calibration frequencies distribution data based on the model and see where there is very little change between frequencies for the antenna pattern. Thus, for instance, for a given antenna configuration on a ship, if at a certain set of frequencies there is very little change in antenna pattern, then one need not sample very many frequencies about this frequency in order to be able to calculate weights for correcting the model data with observed data from shipboard.
In short, one determines the frequencies at which the antenna pattern is changing most rapidly and then uses those weights in a broadband sense for adjacent frequencies within a set band. In order to determine which frequencies the pattern of the ensemble of antennas changes most rapidly, a direction finding algorithm is invoked and a scale model is used to generate the outputs of all of the antennas. These outputs are coupled to a direction finding unit, with the accuracy of the DF bearing line from the source of radiation to the model determining band edge error, i.e., how fast or how slow the pattern changes. In other words, an indirect method is used to determine through the accuracy of the direction finding test which of the frequencies are most important to sample.
In operation, using the scale model, one collects data at a first frequency with the data being sampled at a full complement azimuths angles around 360xc2x0. Now one migrates the calibration frequency and collects data again. The second set of data invokes the direction finding algorithm against the previous frequency and comes up with an RMS error over the 360xc2x0 angles of azimuth for that frequency. This is retained. Then one moves up in frequency a bit and the process is repeated against the first frequency. One is therefore DFing this new set of frequencies that is higher, against the base frequency that was the first one at which data was collected. This process is repeated with ever increasing frequencies until the RMS data approaches or hits an accuracy stop. This is a threshold at which using the original weights the accuracy of the direction finding result is not sufficient. This is called the band edge. One then selects a frequency between the band edge frequency and the original frequency as a delta which is added to the last frequency to arrive at the next calibration frequency.
The result of doing this on an iterative basis is a series of calibration frequencies throughout the entire frequency band of interest and therefore defines the calibration frequency distribution. The process therefore is a base frequency set that is used for the calibration array manifold. This process, in essence, tells one where the 90 calibration frequencies should be.
Note that the reduction in calibration frequencies made possible by the subject invention comes from the realization of the broadband capability of the complex optimization weights. One does not have to know which frequencies to use. It is a finding of the subject invention that there will be a significant reduction of frequencies necessary because one expects these complex weights to have some broadband capability. The broadest band of these complex weights will occur where the frequency set is not dense, whereas more narrow band weights are going to come from those frequency bands having calibration frequencies which are inherently more dense. A selection of which frequencies to use is such that if the frequency distribution were uniform from frequency 1 to frequency 90, then one would simply divide the number of frequencies by, for instance, 10 and use these weights centered around these frequencies.
However, if the original model for which the antennas were characterized indicated that there was a bunching up or increased density of frequencies for which measurements are to be made, and then one concentrates the weights towards those bunched up or highly dense frequency distributions.
Thus, in order to select those frequencies for which a weight is applicable, one looks at the density of the frequencies obtained from the original modeling. Where the density of the frequencies is high, the frequencies selected for the weights is more numerous. This means that the bandwidth of the complex weights utilized by this area will be reduced. For this reduced bandwidth, one would then collect shipboard data at more frequencies than would be indicated from the fundamentally less dense frequency band. Thus, for instance, one might sample 10 frequencies in a dense region, whereas for the rest of the entire frequency band, one might only use 5 frequencies.
It will be appreciated that the exact frequency is not so important for a dense frequency distribution. It is a fact rather that choosing a large number of sample frequencies within that dense frequency range is what is required.
In summary, a system is provided for reducing the time that a ship must be maintained on station to collect calibration data by reducing the frequencies at which calibration data is to be collected. Since it is impractical to consider calibrating over elevation angle and polarization on the full-scale ship, an accurate scale model and test facility are utilized, however, with surface wave data being collected from the ship before model-based data can be utilized. In the subject system, the number of calibration frequencies used aboard ship is dramatically reduced by as much as 80%, thus reducing the time the ship must be on station when doing a calibration run. In one embodiment, the shipboard surface wave data for one elevation and one polarization is combined with surface wave and sky wave data from the scale model to generate an array manifold or database used in subsequent direction finding activities. In order to minimize the frequencies at which shipboard data is collected, the set of frequencies used for shipboard calibration is limited to a subset of all the frequencies used in the calibration. The number of frequencies used for shipboard calibration is reduced by selecting frequencies which are valid over a wide bandwidth.